Project Summary/Abstract Correct spatial and temporal gene expression are essential for many developmental and physiological processes, and gene expression phenotypes are often under stabilizing selection. At the same time, there is extensive variation in DNA regulatory elements in natural populations. In humans, this variation has been associated with a range of diseases as well as individual variation in drug toxicity and efficacy. Predicting the functional consequences of variation in DNA regulatory elements is critical for biomedical research, but complicated. Gene expression is the result of complex interactions between transcription factors, DNA regulatory elements, and components of the basal transcriptional machinery. As a result, the functional consequence of any one change in a regulatory element can depend on what changes are found elsewhere within the same regulatory element. The goal of the proposed research is to understand the impacts that naturally occurring variation in DNA regulatory elements has on transcription factor binding and gene expression. In particular, this project focuses on quantifying the functional consequences of interactions between variants within regulatory elements to understand, in part, the extent to which these interactions may violate the assumptions of additivity that underlie many attempts to link phenotypic and genotypic variation (e.g. Genome-Wide Association Studies). The proposed research makes use of extensive information about combinatorial transcriptional regulation at a set of ~8,000 regulatory elements underlying the expression of mesodermal genes in Drosophila. I will take three complementary approaches to addressing the project goal. First, I will use of ChIP-Seq to quantify the contribution of natural genetic variation to transcription factor binding variation for a set of core mesodermal regulators Drosophila strains for which we have full genomic sequences and extensive expression data (Aim 1). Next, I will conduct population genetic analyses to understand how selection operates on functional regulatory variants and to identify potential interactions among variants within regulatory elements (Aim 2). Finally, I will use the results of Aim 1 and 2 to select candidate regulatory elements in which I will quantify the contributions of variants, and interactions between them, to gene expression variation using in vivo reporter assays. The results of my research will provide essential insights into the relationship between the sequence of regulatory elements and gene expression, improving our ability to predict the consequences of regulatory variation and our understanding of how regulatory DNA evolves within and between populations.